Abstract: To solve the structural parameter identification problem with measurement noises during the construction process of long-span cable-stayed bridges,an entire-processed parameter identification method based on grey-neural network was proposed.The fusion of the grey system theory and the artificial neural network makes it possible to identify and forecast structural parameters even under the condition of insufficient samples or incomplete data.The identification results for the Su-Tong bridge show that with the proposed method the maximum error between post-identification result and real structural response decreases by 77% and the estimation accuracy is raised by 50% than with traditional ones.